Research On Inversion Of Photosynthetic Active Radiation And Leaf Area Index Vertical Distribution In Different Vegetation Canopy

Remote sensing as a new comprehensive detection technology,it has the characteristics of the objective,real-time,nondestructive.Combined with geographic information system and global positioning systems and other modern high and new technology,it can realize the information collection and analysis of timing,quantitative,and positioning.With its strong objectivity and little human disturbance,the accuracy of remote sensing monitoring apply for agricultural and foresty gradually increase.It support more timely and accurate decisions to obtain the information.Photosynthetic Active Radiation is the energy source of plant photosynthesis.It affect plant growth,development,yield and quality.Establish vertical distribution of PAR in canopy and to analyze the relationship with canopy structure and sun’s incident Angle,etc.It can analysis energy utilization in the canopy and inversion Leaf area index quantitatively by remote sensing.Leaf area index is an important vegetation structure parameter.It defined as leaf area per unit surface area.Leaf area index affected by vegetation,age,plant spacing and other factors and it control the biophysical processes of vegetation,such as light interception and PAR distribution within the canopy.In this paper,corn and forest are the research object.Considering the problems existing in the LAI inversion,this paper researched the method of using physical model inversion LAI and its vertical distribution.In this paper,the main content and results are as follow:(1)In this study,it simulated the vertical distribution of PAR in the canopy and analyzed the relationships between PAR and some parameters,such as solar zenith angle,LAD,LAI,maize canopy structure,special for the heterogeneous canopies such as that crop with width and narrow ridges.LAI is inverted using different algorithms in vertical distribution model of PAR transmittance combined with extinction coefficient and then compared with measured values of different height layers.Results showed that the algorithm of Bonhomme&Chartier was proved to be effective for inversion of the vertical distribution of LAI.There were differences in inversion results with different solar zenith angles.In the upper canopy,the solar altitude angle varying from 30 to 45 solar altitude angle could improve LAI estimation accuracy with the RMSE of 0.18,and from 45 to 30 solar altitude angle with the RMSE of 0.30 in the middle canopy,30° and 45° with the RMSE value of 0.11 and 0.09 in the under canopy.The result showed that it had a fairly good agreement between calculated and observed data,which proved the validity of the theoretical model.The result indicates that this model has a high precision simulating the vertical distribution of maize canopy PAR transmittance during the tasseling stage before sealing ridge.In summary,these results demonstrate that the canopy LAI inversion model is better suited for the estimation of summer maize LAI of different height layers.(2)In this study,the vertical distribution of canopy PAR is simulated based on Radiosity-Graphics Combined model(RGM)and the relationships between PAR and the solar zenith angle,LAI and canopy structure are analyzed,especially for heterogeneous canopies such as crops with wide and narrow ridges.Taking maize as the experimental object,the results indicate that this model can simulate the vertical distribution of canopy PAR transmittance from the tasseling stage to the sealing ridge with a high degree of precision.The results show that RGM model invert PAR vertical distribution accuracy and 60? solar elevation angle a higher degree of accuracy,with an RMSE of 0.037307 and 0.064702.The LAI is extracted using different algorithms in a model that describes the vertical distribution of PAR transmittance combined with the extinction coefficient and the extracted values are then compared with measured values for layers at different heights.The results show that the Campbell ellipsoid distribution algorithm with 60? solar elevation angle inverts the LAI with a higher degree of accuracy than Bonhomme and Chartier algorithm for different height layers.(3)In this study,the method of LAI inversion in forest canopy based on combination of PROSAIL model and vegetation index.Used biochemical parameters as the input parameters input to the PROSAIL model to simulate forest spectral reflectance and NDVI-LAI,RVI-LAI prediction model was established.Experiments using the TM7 remote sensing image data,extracted the spectral reflection input predictive model to invert LAI.The results show that the NDVI-LAI logarithm model predicted results are good,with the R2 of 0.8942 and the RMSE value of 0.492903.Compared the NDVI-LAI model with RVI-LAI model,the RVI-LAI linear model predicted results are better,with the R2 of 0.8876 and RMSE value of 0.39.